Learn Graphs and Social Network Analytics Using Python

This course is absolutely designed for beginners , graph enthusiast ready to analyze the world using graphs
Free tutorial
Rating: 4.1 out of 5 (431 ratings)
26,644 students
Learn Graphs and Social Network Analytics Using Python
Free tutorial
Rating: 4.1 out of 5 (431 ratings)
26,644 students
Create graphs using NetworkX package
Create nodes of a graph
Create edges of a graph
Determine the attributes of a node and edges
Analyze social networks like Facebook and Twitter
Students will learn more about properties of a graph
Learn about Clustering coefficient , Betweenness centrality, degree centrality etc
Learn about Connected graphs, Bipartite graphs, etc
Learn about the types of graphs used for social network analysis

Requirements

  • Basic programming knowledge in python or other language
  • Access to computer and with an internet
  • Fundamentals of Graph Theory
Description

BRAND NEW COURSE IS HERE ! Learn Graphs and Social Network Analytics .Become a graph and social analyst today. This is a comprehensive course , simple and straight forward for python enthusiast and those with little python background. You want to learn about how to draw graphs and analyze them, this is the course for you. This course will contain some quizzes, test and some homework assignments, as well as some real world assignment projects. There is over 55 lectures and about 6hours to complete the course. This course comes with live coding screenshots using iPython Notebook .Below is the list of the course summary

- Overivew of networkX

- Install networkX module and iPython Notebooks

- Create nodes

- Add edges to nodes

- Getting attributes from a graph

- Manipulate your graphs ie.; remove nodes /edges

- Create DiGraphs/MultiGraphs/MultiDiGraphs

- Graph Generators

- Graph metrics ; shortest path/clustering coefficient

- Define functions

- Visualize graphs

- Calculate nodes/degree/centrality metrics

- Some random graphs

- Small famous graphs

- Reading and writing graph files

- Social network analysis

- Subgraphs

- Facebook Social Network Analysis

Course goals :

-At the end of the course students should be able to learn some basics of graph theory

- Students should be able to analyze Facebook social networks

- Students should take the simple quizzes

- Students should know what is directed and undirected graphs

- Students should be able to visualize graphs using different graph plots

- You can use this course to analyze the world as a network

- Everything in this world is now connected

- Extract useful information from graphs

Life time access to the course. What are you waiting for? Learn practical graph and social network analytics today that would improve your career and increase your knowledge.

Who this course is for:
  • Beginners who have never programmed in python before
  • Students who are Graph Enthusiast
  • Intermediate python programmers who want to level up their skills
  • Students who want to analyze social networks like Facebook and Twitter
  • Mathematics students who wants to apply their knowledge in Graph Theory
Course content
25 sections • 66 lectures • 6h 23m total length
  • Course Intro
    05:19
  • Github Account
    01:12
  • Overview of networkX
    07:38
  • Graphs
    4 questions
  • NetworkX Basics
    04:30
  • NetworkX Basics
    7 questions
  • Installation of networkX and iPython Notebooks
    07:43
  • Installation of iPython Notebook
    1 question
  • Creating Nodes using networkX
    05:12
  • Adding edges to graphs
    05:36
  • Getting graph properties
    08:08
  • Node manipulation
    04:58
  • Adding attributes to graphs-01
    05:12
  • Adding attributes to graphs-02
    05:08
  • Adding edge attributes to graphs-01
    06:47
  • Adding edge attributes to graphs-02
    04:54
  • Creating DiGraphs-01
    09:05
  • Creating DiGraphs-02
    04:52

Instructor
Spark Developer ,Kafka and Data Scientist
Theophilus Siameh
  • 4.1 Instructor Rating
  • 431 Reviews
  • 26,644 Students
  • 1 Course

I'm Spark Developer ,SAS Programmer and Data Scientist, Predictive Modeler, Graph Analyst and building of Android Mobile Applications . I have Masters degree(Mathematics and Statistics) from East Tennessee State University, Johnson City ,Tennessee . Over the course of my career I have developed a skill set in analyzing data, specifically using Python and a variety of modules and libraries. I hopes to use this experience in teaching and data science to help other people learn the power of the Python programming language and its ability to analyze data,and graph as well as present the data in clear and beautiful visualizations.

I also have the following Certifications :

Databricks and O’Reilly Certified Developer for Apache®Spark™ (2016),

SAS Certified Base Programmer for SAS 9  Certified 02/04/2015

SAS Certified Clinical Trials Programmer Using SAS 9 Certified  06/12/2015

SAS Certified Advanced Programmer for SAS 9 Certified 04/29/2015

SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling Certified 08/25/2015